A multiomics focusing towards the molecular networks of lung development.
A multiomics focusing towards the molecular networks of lung development.
复制标题
专注于肺部发育分子网络的多组学。
DOI：
10.1152/ajplung.00364.2019
复制
发表时间：
2019
期刊：
影响因子：
--
通讯作者：
Clair,Geremy
中科院分区：
文献类型：
--
作者：
Clair,Geremy
在胚胎发育的第一个月末，前肠的一小片细胞开始表达转录因子 NKX2。 1. 这一奇异事件是一系列分子过程的开始，最终将导致成熟肺部的形成。从结构和细胞的角度来看，肺都是异质的。其优雅的分支和肺泡结构的形成需要许多分子和细胞事件的发生。阐明肺部发育的协调对于揭示各种慢性和急性呼吸道疾病的根本原因至关重要。对肺器官发生的探索可能使我们能够对抗疾病并再生受伤的肺部。组学技术的出现和民主化为科学家和临床医生提供了广泛的快速工具来探索发育生物学。描述肺器官发生的组学数据集的数量正在不断增长。每一代新的组学技术都变得更快、更灵敏、更准确，从而提供了有关生物过程的更多细节。迄今为止，转录组学、表观基因组学、蛋白质组学、脂质组学和代谢组学已被用来描述肺器官发生。每项组学研究都会生成丰富的数据集，但不同研究之间选择的时间点以及用于样品制备、保存和处理的方法通常是不同的。因此，整合不同组学研究的结果即使不是不可能，也通常很困难。最近，已经出现了结构化和协调的努力来描述发育中的肺的分子图谱。此类努力的一个突出例子是由国家心肺血液研究所 (NHLBI) (1) 资助的 LungMAP 联盟。 LungMAP 的参与者可以访问集中的人体组织核心和公共动物中心，使不同的群体能够生成协调的多组学数据集。研究人员发现，将新生成的数据集集成到现有数据集的另一种方法是故意设计新研究，以匹配现有研究的全部或部分方法 (2, 9)。总体而言，多层组学的整合提供了比“单一组学”研究更深入的见解。例如，一项整合脂质组学、蛋白质组学和代谢组学的研究表明，脂质组的组成在肺泡化过程中受到显着调节。蛋白质组学和代谢组学数据集中包含的数据确定了导致这些变化的途径 (4)。另一项结合转录组学和蛋白质组学的研究表明，虽然 40% 的 RNA 表达和蛋白质丰度在发育过程中相关，但一些特定途径更容易受到转录后和翻译后调控 (6)。由于敏感性问题，大多数组学分析都是在整个组织匀浆上进行的，对发育过程中发生的分子变化提供了模糊的视图。需要研究关注小尺度上发生的分子过程。最近出现的创新技术使得能够拍摄小至单个细胞的组学快照。单细胞转录组学是最成熟的“单细胞”组学技术，在描述发育过程中细胞异质性的调节方面特别有效 (7)。单细胞表观基因组学、单细胞蛋白质组学和单细胞代谢组学仍处于起步阶段，但正在以令人难以置信的速度发展 (8, 10)。我们正接近令人兴奋的时刻，届时将有可能在单细胞水平上整合多个……
At the end of the first month of embryonic development, a patch of cells of the foregut starts to express the transcription factor NKX2. 1. This singular event is the inception of a cascade of molecular processes that ultimately will lead to the formation of mature lungs. The lungs are heterogeneous both from a structural and a cellular standpoint. The formation of its elegant branched and alveolar structures requires many molecular and cellular events to occur. Elucidating the orchestration of lung development is critical to revealing the underlying causes of a wide range of chronic and acute respiratory diseases. The exploration of lung organogenesis may allow us to fight diseases and to regenerate injured lungs. The appearance and the democratization of omics technologies have empowered scientists and clinicians with a broad range of fast tools to explore developmental biology. The number of omics datasets describing lung organogenesis is continuously growing. With each new generation, omics technologies are faster, more sensitive, and more accurate, thus providing more details on the biological processes at play. To date, transcriptomics, epigenomics, proteomics, lipidomics, and metabolomics have been used to describe lung organogenesis. Each omics study generates rich datasets, but the time points selected as well as the methods used for sample preparation, conservation, and processing are often divergent between studies. As a consequence, it is often hard, if not impossible, to integrate the results from different omics studies. Recently, structured and coordinated efforts have emerged to describe the molecular atlas of the developing lung. A prominent example of such efforts is the LungMAP Consortium, funded by the National Heart, Lung, and Blood Institute (NHLBI)(1). The participants of the LungMAP have access to a centralized human tissue core and to a common animal hub enabling different groups to generate coordinated multiomics datasets. Another way that researchers have found to enable the integration of a newly generated dataset to an existing one is to deliberately design the new study to match all or portions of the methods of the preexisting one (2, 9). Overall, the integration of multiple layers of omics provides deeper insights than “single-omics” studies. For example, a study integrating lipidomics, proteomics, and metabolomics showed that the composition of the lipidome was dramatically modulated during alveolarization; the data comprised in the proteomics and metabolomics datasets identified the pathways responsible for these changes (4). Another study, combining transcriptomics and proteomics, showed that while 40% of RNA expression and protein abundance were correlated during development, some specific pathways were more prone to posttranscriptional and posttranslational regulations (6). Due to sensitivity issues, most omics analyses have been performed on whole tissue homogenate providing a blurred view of the molecular changes occurring during development. Studies are needed to focus on the molecular processes occurring at smaller scales. Innovative technologies have recently emerged, enabling to take omics snapshots at scales down to individual cells. Single-cell transcriptomics is the most mature of the “single-cell” omics technologies and is particularly efficient at describing the modulation of cellular heterogeneity during development (7). Single-cell epigenomics, single-cell proteomics, and single-cell metabolomics are still in their infancy but are progressing at an incredible pace (8, 10). We are nearing the exciting point when it will be possible to integrate, at the single-cell level, multiple …